Spatio-temporal processing for distant speech recognition

A new subband based front-end processor for speech recognition is presented. It integrates both spatial and temporal signal processing methods to enhance noisy signals as a means to reduce the mismatch problem in speech recognition. The approach makes use of the popular blind signal separation (BSS) to spatially separate the target signal from the interference. Due to the multipath/reverberant environment, BSS has its fundamental limitation in the separation quality. To overcome that, an adaptive noise canceller (ANC) is employed to perform further interference reduction. Experimental results show that even in an adverse environment, the proposed structure improves the word recognition rate (WRR) by 70% for the connected digit recognition task.